Conversion probability conditioned on \({\mathsf {SIT}}\)  dimensions.
We investigate the relation between user behaviors and the aforementioned \({\mathsf {SIT}}\) -based measures: \(\#\)\({\mathsf {CC}}\) , \({\mathsf {GS}}\) , \({\mathsf {GPR}}\) , \({\mathsf {GPPR}}\) , \({\mathsf {UGT}}\) , and \({\mathsf {IGT}}\) . Due to space limitations, we only report the analysis results on FPS, and the rest datasets derive similar results.
Following the setting of [1]}, we employ the density-based discretization to convert the scores of \({\mathsf {SIT}}\) -based measures into five different levels, where a higher level indicates a larger score.
Moreover, we use conversion probability [1]}, [3]} to evaluate how the user acts. In particular, given a level of certain \({\mathsf {SIT}}\)  measure, the adoption (resp. invitation) conversion probability is the fraction of source-target pairs existing adoption (resp. invitation) behaviors over all pairs in this level.
